Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, USA.
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, USA.
Ann Work Expo Health. 2018 Mar 12;62(3):259-268. doi: 10.1093/annweh/wxx112.
Little is known about how mobile populations of workers may influence the ability to implement, measure, and evaluate health and safety interventions delivered at worksites.
A simulation study is used to objectively measure both precision and relative bias of six different analytic methods as a function of the amount of mobility observed in the workforce. Those six methods are then used to reanalyze a previously conducted cluster-randomized control trial involving a highly mobile workforce in the construction industry.
As workforce mobility increases, relative bias in treatment effects derived from standard models to analyze cluster-randomized trials also increases. Controlling for amount of time exposed to the intervention can greatly reduce this bias. Analyzing only subsets of workers who exhibit the least amount of mobility can result in decreased precision of treatment effect estimates. We demonstrate a 59% increase in the treatment effect size from the reanalysis of the previously conducted trial.
When evaluating organizational interventions implemented at specific worksites by measuring perceptions and outcomes of workers present at those sites, researchers should consider the effects that the mobility of the workforce may have on the estimated treatment effects. The choice of analytic method can greatly affect both precision and accuracy of estimates.
对于流动人口如何影响在工作场所实施、衡量和评估健康和安全干预措施的能力,人们知之甚少。
采用模拟研究的方法,根据劳动力中观察到的流动程度,客观地衡量六种不同分析方法的精度和相对偏差。然后,我们使用这六种方法重新分析了之前在建筑行业中进行的一项涉及高度流动劳动力的集群随机对照试验。
随着劳动力流动的增加,用于分析集群随机试验的标准模型得出的治疗效果的相对偏差也会增加。控制接触干预的时间可以大大减少这种偏差。仅分析表现出最少流动性的工人子集可能会导致治疗效果估计的精度降低。我们从之前进行的试验的重新分析中得出,治疗效果大小增加了 59%。
当通过测量特定工作场所的工人的感知和结果来评估在特定工作场所实施的组织干预措施时,研究人员应考虑劳动力流动可能对估计的治疗效果产生的影响。分析方法的选择会极大地影响估计的精度和准确性。